AI-900日本語 dumps materials - exam dumps for AI-900日本語: Microsoft Azure AI Fundamentals (AI-900日本語版)

Microsoft Azure AI Fundamentals (AI-900日本語版) - AI-900日本語 certification

Exam Code: AI-900J

Exam Name: Microsoft Azure AI Fundamentals (AI-900日本語版)

Updated: Sep 13, 2026

Q & A: 336 Questions and Answers

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Although the Microsoft AI-900 exam is associated with the foundational-level certification, all the successful candidates can pursue various lucrative career paths in the field of IT. Some of the job roles that these professionals can work in include a Data Scientist, a Software Developer, and an Azure AI Engineer, among others. They can also proceed to get some other role-based certificates to boost their potential in the world of Information Technology. With the Microsoft Certified: Azure AI Fundamentals certification, you can earn an average of $48,000 per annum as an entry-level specialist. Those with some work experience can get an average of $74,000 per year.

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Certification Path

The Azure AI Fundamentals certification might not be a prerequisite for any other certification levels, however, it can still be used to prepare for multiple Azure-related qualifications including the Microsoft Certified: Azure Data Scientist Associate and the Microsoft Certified: Azure AI Engineer Associate.

Reference: https://docs.microsoft.com/en-us/learn/certifications/exams/ai-900

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The Microsoft AI-900 exam, usually known as the Microsoft Azure AI Fundamentals, is well suited to baseline-level IT specialists with knowledge of artificial intelligence (AI) & Machine Learning (ML), and the relevant Microsoft Azure concepts. This is the only test that you should pass to qualify for the Microsoft Certified: Azure AI Fundamentals certification.

Microsoft AI-900日本語 Exam Syllabus Topics:

SectionWeightObjectives
Features of generative AI workloads on Azure20–25%- Describe responsible AI practices for generative AI
- Describe generative AI concepts
- Describe capabilities of Azure OpenAI Service
- Describe use cases for generative AI
Features of computer vision workloads on Azure15–20%- Identify types of computer vision solutions
- Describe capabilities of Azure Computer Vision
- Describe capabilities of Azure Custom Vision
- Describe capabilities of Azure Form Recognizer
- Describe capabilities of Azure Face
Features of Natural Language Processing (NLP) workloads on Azure15–20%- Identify types of NLP solutions
- Describe capabilities of Azure Speech
- Describe capabilities of Azure Translator
- Describe capabilities of Azure Language
Fundamental principles of machine learning on Azure15–20%- Describe automated machine learning
- Describe core concepts of machine learning
- Describe machine learning pipelines
- Describe capabilities of Azure Machine Learning
Artificial Intelligence workloads and considerations15–20%- Identify types of AI workloads
- Describe responsible AI principles
- Describe considerations for developing AI solutions

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